The first draft drops in minutes. The project looks almost done. Honestly, that is an illusion. Engineers spend days fixing logical flaws, bridging context gaps, and fighting integration bugs. Traditional sprint math ignores this massive workload shift.
Project estimation must change. Standard story points fail with AI. Today, tech leaders use AI to estimate the work. The speakers will unpack how models analyze historical data, predict hidden technical debt, and calculate realistic delivery windows.
Look at the actual numbers. They will dissect real cases from their pipelines. You walk away with a hard framework to recalculate budgets and set deadlines that hold up in the real world.
📅 Date & Time
🗓️ September 16
📍 Online Event
🕒 15:00 EDT (New York) | 21:00 CEST (Berlin)
🎙️ Speakers
Yuriy Diachenko – CEO at MIF Projects, Technical leadership. Manages engineering teams through modern tech transitions with 15+ years of experience.
Igor Omelianchuk – Tech & R&D Expert, CEO at Corsac Tech. Works with AI solutions in production across complex platforms.
Andrew Lychuk – Fractional CTO & IT Infrastructure Strategist. Focuses on mitigating technical debt and guiding teams through architectural changes.
💡 Key points we’ll cover
- How to update traditional estimation models for AI-driven development.
- Specific project phases that take longer when engineers rely on AI.
- Calculating the hidden financial costs of refactoring and integration.
- Hard frameworks to set realistic budgets and delivery dates.
- Why AI creates severe estimation risks for production releases.
🔎 Who should attend?
- Founders, CTOs, and tech leaders.
- Product and Engineering managers handling AI-assisted teams.
- Delivery and R&D Managers focused on prototyping, legacy modernization, or core product development.
👉 Reserve your spot now. Learn how to accurately estimate project timelines before committing to unrealistic deadlines.